SON Interfrequency Neighbor Planning for Load Balancing
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Solution Overview
Problem
Current telecommunications networks face inefficiencies due to static neighbor relations between frequency carriers, leading to suboptimal load balancing, which can result in dropped calls, packets, and poor network performance.
Innovation Solution
A network device with a policy engine that identifies network condition scenarios requiring updated neighbor associations, locates associated policies, and provides configuration directives to the telecommunication engine to reassign loaded carriers to less loaded ones, optimizing carrier associations dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static neighbor relations are used between frequency carriers, then network configuration is simple and stable, but load balancing performance deteriorates leading to dropped calls and packets
Solution Approach 1:
The patent implements dynamic neighbor relations where the network device monitors carrier load conditions and automatically updates neighbor associations based on real-time traffic patterns. This transforms the static neighbor relation configuration into a dynamic system that adapts to changing network conditions, improving load balancing and call completion rates while maintaining manageable complexity through automated policies.
Solution Approach 2:
The network device performs self-optimization by automatically detecting when load balancing performance degrades and autonomously updating neighbor relations without manual intervention. The system monitors its own performance metrics and applies corrective configurations, enabling self-service optimization that improves reliability without proportionally increasing operational complexity.
2Productivity
If dynamic carrier reassignment is implemented, then load balancing performance improves, but network control complexity increases
Solution Approach 1:
The patent establishes predefined policies and thresholds for carrier reassignment before dynamic optimization begins. These preliminary configurations include load threshold values, carrier priority settings, and reassignment rules that guide the dynamic optimization process. This preliminary setup enables automated decision-making that improves network efficiency while containing complexity through structured, pre-planned optimization criteria.
Solution Approach 2:
The system dynamically changes operational parameters such as neighbor association lists and carrier selection criteria based on monitored network conditions. By adjusting these parameters automatically according to predefined policies, the system achieves improved load balancing and network efficiency while managing complexity through parameter-based control rather than structural complexity.
3Loss of time
If manual neighbor association updates are performed, then configuration precision is high, but time consumption increases leading to slower response to network conditions
Solution Approach 1:
The network device automatically monitors its own performance metrics and triggers neighbor association updates when degradation is detected, eliminating the need for manual intervention. This self-service approach responds immediately to network conditions, reducing response time while maintaining configuration accuracy through automated decision logic and predefined optimization policies.
Solution Approach 2:
The system implements continuous monitoring of network performance metrics and uses this feedback to automatically trigger neighbor association updates when performance thresholds are breached. This closed-loop feedback mechanism ensures rapid response to changing network conditions while maintaining configuration precision through data-driven decision-making and validation against optimization goals.
Data Source
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AI summary
In an example, a self-organizing network (SON) provides automated interfrequency load balancing for a base station such as a NodeB. The NodeB may provide a plurality of carriers, such as in a plurality of UARFCN frequencies, and the SON may provide configuration directives for increasing efficiency. For example, when one carrier becomes loaded, the SON may update neighbor associations to take advantage of relatively unloaded frequency carriers. A plurality of scenarios S may be provided, and a policy P may be defined for each. When the NodeB encounters a scenario S, SON may send configuration directives to implement policy P. Similar concept and policy could be applied in conjunction with INTER Technology Neighbor Definitions between LTE and UMTS and UMTS and GSM. Example if GSM Frequency Neighbors needs to be replaced with different Frequency Neighbors from UMTS based on Load or RF conditions.